1. Field of the Invention
The present invention relates generally to a method of generating anti-collusion fingerprint codes using (na, n2a−2, na−1, n, 0, 1) GD-PBIBD. That is, the present invention relates to a digital fingerprinting method for protecting the copyrights of digital content or preventing the illegal distribution and use of digital content and, more particularly, to a method of generating fingerprint codes, which is a key technology in digital fingerprinting. By inserting fingerprint codes, generated by the present invention, into images, video and audio, which are digital media, copyrights can be protected, that is, the illegal use of digital content can be prevented, and a user connected with illegal distribution can be searched for in the event of illegal distribution of legal content.
2. Description of the Related Art
Digital fingerprinting is technology for preventing illegal distribution and subsequent use by inserting fingerprints, that is, unique information about purchasers who purchase digital content, such as text, images, video, audio, etc., into the digital content. Digital fingerprinting is technology that is used in such a manner as to insert a purchaser's unique fingerprint into content sold to the purchaser, extract the fingerprint from the content at the time of exposing the illegal distribution or use of the content, find the illegal distributor or user, and take legal action or another measure.
In digital fingerprinting, fingerprint information, modulated in a noise form, is inserted into original content, therefore the digital fingerprinting may be susceptible to various types of attacks in attempts to remove inserted fingerprints. In particular, in digital fingerprinting, the fingerprints of different users are inserted into the same original content, with the result that respective users have different pieces of content. As a result, two or more users can easily determine the differences between respective pieces of content by comparing the respective pieces of content, and inserted fingerprints can be easily removed using the differences.
Among the various attacks, an averaging attack is one of the most effective methods of weakening fingerprints that are inserted into content in a noise form. The averaging attack is a collusion attack that is most easily applicable to images or video to which the fingerprinting technique has been applied, and is an attack method of generating a new image or frame by averaging two or more images or video frames into which different fingerprints have been inserted. The averaging attack exhibits the effect of reducing fingerprints to an extent that is proportional to the number of pieces of content that are used in the attack. The overall intensity of an inserted fingerprint signal is reduced by the averaging attack, therefore purchaser information is not extracted, or erroneous information is extracted, at the time of extracting a fingerprint. To be immune to an averaging attack, a fingerprinting system must identify the purchasers involved in the attack and provide notification of information about the purchasers with respect to the content on which the averaging attack was made. Fingerprint information inserted for that purpose must be codes that are immune to an averaging attack.
In order to generate fingerprint codes immune to a conventional averaging attack, Group Divisible Partially Balanced Incomplete Block Design (GD-PBIBD), which pertains to the field of a set design theory, has been employed. Codes, generated based on the design theory, have features that are robust to averaging attacks due to the features of the design theory. However, in the generation of codes, only codes disclosed in documents have been used, therefore only a limited number of codes can be used due to the characteristics of document material, and the number of users that can be accommodated is considerably limited.